Chapter 2: Study Design

Overview

  • 2 Study design
  • 2.1 Sampling principles and strategies
    • 2.1.1 Populations and samples
    • 2.1.2 Parameters and statistics
    • 2.1.3 Anecdotal evidence
    • 2.1.4 Sampling from a population
  • 2.2 Experiments
    • 2.2.1 Principles of experimental design
    • 2.2.2 Reducing bias in human experiments
  • 2.3 Observational studies

2.1 Sampling principles and strategies

2.1.1 Populations and samples

Research Question: What is the average mercury content in swordfish in the Atlantic Ocean?

  • The population of interest is all the swordfish in the Atlantic Ocean.
  • Researchers collect a sample of 60 swordfish and measure their mercury content.

2.1.2 Parameters and statistics

Research Question: What is the average mercury content in swordfish in the Atlantic Ocean?

  • The population of interest is all the swordfish in the Atlantic Ocean.
  • Researchers collect a sample of 60 swordfish and measure their mercury content.
    • They calculate the average mercury content of the swordfish in this sample. This number is a statistic.
  • This statistic is an estimate of a parameter, the true average mercury content of all swordfish in the Atlantic.

Key point: Statistics are calculated from a sample, while parameters are properties of the entire population.

2.1.3 Anecdotal evidence

An example of faulty reasoning:

A man on the news got mercury poisoning from eating swordfish, so the average mercury concentration in swordfish must be dangerously high.

  • This fallacy relies on anecdotal evidence.
  • Such evidence may be true and verifiable, but it may only represent extraordinary cases and therefore not be a good representation of the population.
  • Good statistical studies collect a sample of data from a specified population in systematic ways.

2.1.4 Sampling from a population

Research Question: Over the last five years, what is the average time to complete a degree for Duke undergrads?

  • Random selection: Write each graduate’s name on a raffle ticket and draw 10 tickets (or use a computer to generate 10 random names). The selected names would represent a random sample of 10 graduates.
  • Such a sample is called a simple random sample.
  • This is best way to collect a sample, because it avoids sampling bias.
  • Simple random samples are the best way to get sample that is representative of the entire population.

Convenience Samples

Research Question: Over the last five years, what is the average time to complete a degree for Duke undergrads?

  • Suppose that Duke did a poor job keeping track of its graduates, except for the health sciences departments.
  • We might find it convenient to just use the data we can get, rather than taking a true random sample of the whole population.
  • Convenience samples collected in this way often suffer from sampling bias.

2.2 Experiments

2.2.1 Principles of experimental design

2.2.2 Reducing bias in human experiments

2.3 Observational studies

Group Discussion